Query Health:Distributed Population Queries Update & Demo from ONC’s Office of Standards & Interoperability Rich Elmore Coordinator, Query Health
Objectives Provide a look at how Query Health is progressing • How do the different parts of the Query Health solution fit together? • How might a distributed query work in a real technical environment?
Vision Enable a learning health system to understand population measures of health, performance, disease and quality, while respecting patient privacy, to improve patient and population health and reduce costs.
Distributed queries unambiguously define a population from a larger set Questions about disease outbreaks, prevention activities, health research, quality measures, etc.
Distributed Query NetworksVoluntary, No Central Planning Community of participants that voluntarily agree to interact with each other. There will be many networks; requestors and responders may participate in multiple networks. Query Requestors Participating Responders
New York City / New York State Pilot Dr. Michael Buck, Primary Care Information Project
How would a distributed query work? Aggregated Data Patient Data Note: All patient level data stays behind the firewall. Data Source Information Requester Query & Results Reviewer 1. EHR / Clinical Record (Patient Data) Translate patient data 3. Distribute Query to Data Sources 2. Query Health Data Model 5. Sends Query Results to Information Requestor 4. Execute Query , format & return Results Responding Organization Firewall
Type II DiabetesExpanded Analysis Example Result Set Example Result Set
New York City / New York State Pilot Information Requestors Data Sources Axolotl RHIO NYC PCIP Sends Query to Data Sources Distributes Query Results to Information Requestor Inter-systems RHIO NYS DOH Sends Query to Data Sources Distributes Query Results to Information Requestor eCWEHR
The QueryNew HQMF • Health Quality Measure Format • HQMF newly modified to support the needs for dynamic population queries: • More executable • Simplified • Advantages for query • Avoids “yet another standard” • Secure (vs procedural approach) • Works across diverse platforms • Benefits – Speed and Cost
The Query Envelope • Query agnostic • Content agnostic • Metadata facilitates privacy guidance from HIT Policy Committee • RESTful interface specification
The DataClinical Element Data Dictionary • Advance Directive • Vital Signs • Physical Exam • Family History • Social History • Order • Result • Medical Equipment • Care Setting • Enrollment • Facility • Demographic • Patient Contact Information • Payer Information • Healthcare Provider • Allergies & Adverse Reactions • Encounter • Surgery • Diagnosis • Medication • Procedure • Immunization • ONC S&I Framework deliverable • Standards independent • UML representation underway
The ResultsNew QRDA • Quality Reporting Document Architecture • Category I – Patient Level • Category II – Patient Populations • Category III – Population Measures • Query Health will use new definitions of Categories II and III • Not yet specified and balloted • Needs implementation guide • Needs to align with eMeasures
The path to critical mass • Today, distributed queries are generally limited to • Organizations with large IT & research budgets • Some exceptions (e.g., NYC PCIP, MDPHNet) • Missing: Primary Care, FQHCs, CAHs, HIEs, etc… In other words, most places where clinical care is delivered and recorded • Path to critical mass depends on • Query Health Standards • Health IT vendor participation Health IT vendors Allscripts Amazing Charts AZZLY Cerner dbMotionClinicalWorks Epic eRECORDS IBEZA InterSystems Medicity Microsoft National Health Data Systems NextGenRelayHealth Siemens Check back - more to come at QueryHealth.org
DemonstrationDistributed Query Execution • What you’ll see • Life cycle of a Distributed Query (1 requestor, 2 data providers) • Policy Enablement Layer (control of queries execution and results by data providers) – RESTful interface • Query Envelope metadata for work flow integration and policy enforcement • Integration of hQuery (Query execution) and PopMedNet (policy enablement) • Open source components • Presenting • Marc Hadley, MITRE Corporation • Rob Rosen, Lincoln Peak
DemonstrationQuery Language • What you’ll see • Query Composition using i2B2 query builder • Query representation of i2B2 using internal formats and ontologies • Translation of composed Query to new HQMF • Translation of new HQMF to SQL • Open source components • Presenting • Shawn Murphy, Partners Healthcare • Keith Boone, GE Healthcare